distilbert_lda_100_v1_qqp
This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_100_v1 on the GLUE QQP dataset. It achieves the following results on the evaluation set:
- Loss: 0.3133
- Accuracy: 0.8600
- F1: 0.8240
- Combined Score: 0.8420
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
---|---|---|---|---|---|---|
0.4043 | 1.0 | 1422 | 0.3275 | 0.8511 | 0.7992 | 0.8252 |
0.2918 | 2.0 | 2844 | 0.3133 | 0.8600 | 0.8240 | 0.8420 |
0.2305 | 3.0 | 4266 | 0.3147 | 0.8715 | 0.8340 | 0.8527 |
0.179 | 4.0 | 5688 | 0.3178 | 0.8760 | 0.8279 | 0.8520 |
0.1389 | 5.0 | 7110 | 0.3525 | 0.8805 | 0.8365 | 0.8585 |
0.1067 | 6.0 | 8532 | 0.3905 | 0.8783 | 0.8409 | 0.8596 |
0.086 | 7.0 | 9954 | 0.4037 | 0.8788 | 0.8427 | 0.8608 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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Model tree for gokulsrinivasagan/distilbert_lda_100_v1_qqp
Base model
gokulsrinivasagan/distilbert_lda_100_v1Dataset used to train gokulsrinivasagan/distilbert_lda_100_v1_qqp
Evaluation results
- Accuracy on GLUE QQPself-reported0.860
- F1 on GLUE QQPself-reported0.824